95 results
(View BibTeX file of all listed publications)

**Nonlinear functional causal models for distinguishing cause from effect**
In *Statistics and Causality: Methods for Applied Empirical Research*, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

**Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke**
World Molecular Imaging Conference, 2016 (talk)

**Advances in computational imaging: Benchmarking Deblurring Algorithms, Deep Neural Inpainting, Depth Estimation from Light Fields**
Eberhard Karls Universität Tübingen, Germany, 2016 (phdthesis)

**A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis**
In *Brain-Computer Interfaces: Lab Experiments to Real-World Applications*, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

**Tractable Structured Prediction using the Permutohedral Lattice**
ETH Zurich, 2016 (phdthesis)

**Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy**
World Molecular Imaging Conference, 2016 (talk)

**Markerless tracking of Dynamic 3D Scans of Faces**
In *Dynamic Faces: Insights from Experiments and Computation*, pages: 255-276, (Editors: Curio, C., Bülthoff, H. H. and Giese, M. A.), MIT Press, Cambridge, MA, USA, December 2010 (inbook)

**Policy Gradient Methods**
In *Encyclopedia of Machine Learning*, pages: 774-776, (Editors: Sammut, C. and Webb, G. I.), Springer, Berlin, Germany, December 2010 (inbook)

**Approximate Inference in Graphical Models**
University of Cambridge, November 2010 (phdthesis)

**Comparative Quantitative Evaluation of MR-Based Attenuation Correction Methods in Combined Brain PET/MR**
2010(M08-4), 2010 Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), November 2010 (talk)

**Bayesian Inference and Experimental Design for Large Generalised Linear Models**
Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

**Statistical image analysis and percolation theory**
73rd Annual Meeting of the Institute of Mathematical Statistics (IMS), August 2010 (talk)

**Inferring High-Dimensional Causal Relations using Free Probability Theory**
Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

**Statistical image analysis and percolation theory**
28th European Meeting of Statisticians (EMS), August 2010 (talk)

**Predictive Representations For Sequential Decision Making Under Uncertainty**
Université Laval, Quebec, Canada, July 2010 (phdthesis)

**Cooperative Cuts: Graph Cuts with Submodular Edge Weights**
24th European Conference on Operational Research (EURO XXIV), July 2010 (talk)

**Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data**
Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

**BCI and robotics framework for stroke rehabilitation**
4th International BCI Meeting, June 2010 (talk)

**Solving Large-Scale Nonnegative Least Squares**
16th Conference of the International Linear Algebra Society (ILAS), June 2010 (talk)

**Matrix Approximation Problems**
EU Regional School: Rheinisch-Westf{\"a}lische Technische Hochschule Aachen, May 2010 (talk)

**BCI2000 and Python**
Invited lecture at the 7th International BCI2000 Workshop, Pacific Grove, CA, USA, May 2010 (talk)

**Extending BCI2000 Functionality with Your Own C++ Code**
Invited lecture at the 7th International BCI2000 Workshop, Pacific Grove, CA, USA, May 2010 (talk)

**Machine-Learning Methods for Decoding Intentional Brain States**
Symposium "Non-Invasive Brain Computer Interfaces: Current Developments and Applications" (BIOMAG), March 2010 (talk)

**PAC-Bayesian Analysis in Unsupervised Learning**
Foundations and New Trends of PAC Bayesian Learning Workshop, March 2010 (talk)

**Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET)**
Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

**Learning Motor Primitives for Robotics**
EVENT Lab: Reinforcement Learning in Robotics and Virtual Reality, January 2010 (talk)

**Learning Continuous Grasp Affordances by Sensorimotor Exploration**
In *From Motor Learning to Interaction Learning in Robots*, pages: 451-465, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**Imitation and Reinforcement Learning for Motor Primitives with Perceptual Coupling**
In *From Motor Learning to Interaction Learning in Robots*, pages: 209-225, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**From Motor Learning to Interaction Learning in Robots**
In *From Motor Learning to Interaction Learning in Robots*, pages: 1-12, Studies in Computational Intelligence ; 264, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**Real-Time Local GP Model Learning**
In *From Motor Learning to Interaction Learning in Robots*, 264, pages: 193-207, Studies in Computational Intelligence, (Editors: Sigaud, O. and Peters, J.), Springer, Berlin, Germany, January 2010 (inbook)

**Finding Gene-Gene Interactions using Support Vector Machines**
Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

**Accurate Prediction of Protein-Coding Genes with Discriminative Learning Techniques**
Technische Universität Berlin, Germany, 2010 (phdthesis)

**Machine Learning Methods for Automatic Image Colorization**
In *Computational Photography: Methods and Applications*, pages: 395-418, Digital Imaging and Computer Vision, (Editors: Lukac, R.), CRC Press, Boca Raton, FL, USA, 2010 (inbook)

**Quantitative Positron Emission Tomography with a Combined PET/MR System**
University of Oxford, UK, 2010 (phdthesis)

**Structural and Relational Data Mining for Systems Biology Applications**
Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

**Population Coding in the Visual System: Statistical Methods and Theory**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**Bayesian Methods for Neural Data Analysis**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**Approaches Based on Support Vector Machine to Classification of Remote Sensing Data**
In *Handbook of Pattern Recognition and Computer Vision*, pages: 329-352, (Editors: Chen, C.H.), ICP, London, UK, 2010 (inbook)

**Clustering with Neighborhood Graphs**
Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

**Detecting and modeling time shifts in microarray time series data applying Gaussian processes**
Eberhard Karls Universität Tübingen, Germany, 2010 (thesis)

**Detecting the mincut in sparse random graphs
**
Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

**A wider view on encoding and decoding in the visual brain-computer interface speller system**
Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

**A Kernel Method for the Two-Sample-Problem**
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

**Ab-initio gene finding using machine learning**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Reinforcement Learning by Reward-Weighted Regression**
NIPS Workshop: Towards a New Reinforcement Learning? , December 2006 (talk)

**Graph boosting for molecular QSAR analysis**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions**
NIPS Workshop on Causality and Feature Selection, December 2006 (talk)

**Learning Optimal EEG Features Across Time, Frequency and Space**
NIPS Workshop on Current Trends in Brain-Computer Interfacing, December 2006 (talk)

**Semi-Supervised Learning**
Advanced Methods in Sequence Analysis Lectures, November 2006 (talk)

**Prediction of Protein Function from Networks**
In *Semi-Supervised Learning*, pages: 361-376, Adaptive Computation and Machine Learning, (Editors: Chapelle, O. , B. Schölkopf, A. Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)